dgl.DGLGraph.edges¶
-
property
DGLGraph.
edges
¶ Return an edge view
One can use it for:
Getting the edges for a single edge type. In this case, it can take the following optional arguments:
- formstr, optional
The return form, which can be one of the following:
'uv'
(default): The returned result is a 2-tuple of 1D tensors \((U, V)\), representing the source and destination nodes of all edges. For each \(i\), \((U[i], V[i])\) forms an edge.'eid'
: The returned result is a 1D tensor \(EID\), representing the IDs of all edges.'all'
: The returned result is a 3-tuple of 1D tensors \((U, V, EID)\), representing the source nodes, destination nodes and IDs of all edges. For each \(i\), \((U[i], V[i])\) forms an edge with ID \(EID[i]\).
- orderstr, optional
The order of the returned edges, which can be one of the following:
'eid'
(default): The edges are sorted by their IDs.'srcdst'
: The edges are sorted first by their source node IDs and then by their destination node IDs to break ties.
- etypestr or tuple of str, optional
The edge type for query, which can be an edge type (str) or a canonical edge type (3-tuple of str). When an edge type appears in multiple canonical edge types, one must use a canonical edge type. If the graph has multiple edge types, one must specify the argument. Otherwise, it can be omitted.
Setting/getting features for all edges of a single edge type. To set/get a feature
feat
for edges of typeetype
in a graphg
, one can useg.edges[etype].data[feat]
.
Examples
The following example uses PyTorch backend.
>>> import dgl >>> import torch
Get the Edges for a Single Edge Type
Create a graph with a single edge type.
>>> g = dgl.graph((torch.tensor([1, 0, 0]), torch.tensor([1, 1, 0]))) >>> g.edges() (tensor([1, 0, 0]), tensor([1, 1, 0]))
Specify a different value for
form
andorder
.>>> g.edges(form='all', order='srcdst') (tensor([0, 0, 1]), tensor([0, 1, 1]), tensor([2, 1, 0]))
For a graph of multiple edge types, it is required to specify the edge type in query.
>>> hg = dgl.heterograph({ ... ('user', 'follows', 'user'): (torch.tensor([0, 1]), torch.tensor([1, 2])), ... ('user', 'plays', 'game'): (torch.tensor([3, 4]), torch.tensor([5, 6])) ... }) >>> hg.edges(etype='plays') (tensor([3, 4]), tensor([5, 6]))
Set/get Features for All Edges of a Single Edge Type
Create a heterogeneous graph of two edge types.
>>> hg = dgl.heterograph({ ... ('user', 'follows', 'user'): (torch.tensor([0, 1]), torch.tensor([1, 2])), ... ('user', 'plays', 'game'): (torch.tensor([3, 4]), torch.tensor([5, 6])) ... })
Set and get a feature ‘h’ for all edges of a single type in the heterogeneous graph.
>>> hg.edges['follows'].data['h'] = torch.ones(2, 1) >>> hg.edges['follows'].data['h'] tensor([[1.], [1.]])
To set edge features for a graph with a single edge type, use
DGLGraph.edata()
.See also